Consideration of computer limitations in implementing on-line controls

A formal statement of the optimal control problem which includes the interval of dicretization as an optimization parameter, and extend this to include selection of a control algorithm as part of the optimization procedure, is formulated. The performance of the scalar linear system depends on the discretization interval. Discrete-time versions of the output feedback regulator and an optimal compensator, and the use of these results in presenting an example of a system for which fast partial-state-feedback control better minimizes a quadratic cost than either a full-state feedback control or a compensator, are developed

An investigative study into the influence of a commercially available carbohydrate-protein-electrolyte beverage on short term repeated exercise performance

Background: The purpose of this study was to undertake an independent investigation into the effects of ingesting a carbohydrate-protein-electrolyte (CPE) beverage on repeated submaximal and time-trial cycling performance. Methods: Sixteen recreationally trained males (height: 1.76 +/- 0.07 m; weight: 70.05 +/- 7.90 kg; VO2max: 49.69 +/- 4.19 ml.kg1.min1) performed two exercise trials separated by 7 days. Each trial comprised two bouts of 90 minutes exercise separated by a 2 hour recovery period. Each bout comprised 45 minutes exercise on a cycle-ergometer at 60%VO2max (ST), followed immediately by a 45 minute performance test (PT). Participants were randomly assigned an 8% CPE beverage or colour/taste matched placebo (PL) prior to each trial. Participants consumed 100 ml of the assigned beverage every 10 minutes during each ST, and 500 ml at 0 and 60 minutes into recovery (total caloric delivery per trial: 617.6 kcal for CPE and12.8 kcal for PL). Mean power output (W), speed (km.hr1) and distance covered (km) were assessed throughout both trials. Expired air was sampled at 10 minute intervals throughout ST. Blood glucose and lactate were assessed during ST and recovery. RESULTS: Distance covered during ST was significantly reduced with PL by 9.12% (20.18 +/- 0.28 km in ST1 v 18.34 +/- 0.36 km in ST2; P = 0.0001). With CPE, distance covered, power output and average speed were maintained between ST1 and ST2. Oxygen uptake was not significantly different between ST1 and ST2, or conditions. Respiratory exchange ratio (RER) values decreased from 0.98 +/- 0.02 in ST1 to 0.91 +/- 0.02 in ST2 for PL (P = 0.003), supporting reduced total carbohydrate oxidation rates (P = 0.007). Mean blood glucose was maintained in CPE across ST trials, and was significantly greater than PL in ST2 (4.77 +/- 0.09 mmol.L1 for CPE compared with 4.18 +/- 0.06 mmol.L1 for PL, P <0.001). Mean distance during PT2 was 2.96 km (or 17.1%) further with CPE than PL (P = 0.003). Mean power significantly decreased across PT with PL (134.21 +/- 4.79 W and 106.90 +/- 3.25 W, respectively; P <0.04). Conclusions: The use of a CPE beverage improves short-term repeated exercise and subsequent performance compared to PL. Higher rates of carbohydrate oxidation, maintenance of plasma glucose, and decreased levels of fatigue may be beneficial for secondary bouts of performance and faster recovery turnover.Peer reviewe

A New Method for Exposing Deposit Feeders to Contaminated Sediments for Food Chain Studies

(excerpt) The ubiquity and refractory nature of certain organic compounds, such as chlorinated pesticides and polychlorinated biphenyls (PCB\u27s), results in their accumulation in aquatic sediments (Holdrinet et al. 1978, Peck et al. 1980, Wang et al. 1979). Their continuous release from this reservoir through physico-chemical and biogenic processes to the overlying water column results in the accumulation of xenobiotic compounds in the food chain

Multibody Interplanetary Swingby Trajectories /MIST-1/

Computer program incorporates new isolation procedure to determine interplanetary trajectories which utilize a maximum of three flybys. Program also computes singe planet flybys and direct transfer trajectories. The three principle systems employed in MIST-1 use as their fundamental plane the mean plane of the earth's orbit around the sun

General tooth boundary conditions for equation free modelling

We are developing a framework for multiscale computation which enables models at a ``microscopic'' level of description, for example Lattice Boltzmann, Monte Carlo or Molecular Dynamics simulators, to perform modelling tasks at ``macroscopic'' length scales of interest. The plan is to use the microscopic rules restricted to small "patches" of the domain, the "teeth'', using interpolation to bridge the "gaps". Here we explore general boundary conditions coupling the widely separated ``teeth'' of the microscopic simulation that achieve high order accuracy over the macroscale. We present the simplest case when the microscopic simulator is the quintessential example of a partial differential equation. We argue that classic high-order interpolation of the macroscopic field provides the correct forcing in whatever boundary condition is required by the microsimulator. Such interpolation leads to Tooth Boundary Conditions which achieve arbitrarily high-order consistency. The high-order consistency is demonstrated on a class of linear partial differential equations in two ways: firstly through the eigenvalues of the scheme for selected numerical problems; and secondly using the dynamical systems approach of holistic discretisation on a general class of linear \textsc{pde}s. Analytic modelling shows that, for a wide class of microscopic systems, the subgrid fields and the effective macroscopic model are largely independent of the tooth size and the particular tooth boundary conditions. When applied to patches of microscopic simulations these tooth boundary conditions promise efficient macroscale simulation. We expect the same approach will also accurately couple patch simulations in higher spatial dimensions.Comment: 22 page

The prevalence and properties of cold gas inflows and outflows around galaxies in the local Universe

We perform a stacking analysis of the neutral \nad\,$\lambda\lambda$5889,5895\,\AA\ ISM doublet using the SDSS DR7 spectroscopic data set to probe the prevalence and characteristics of cold (T\,$\lesssim$\,10$^{4}$\,K) galactic-scale gas flows in local (0.025$\leqslant z\leqslant$0.1) inactive and AGN-host galaxies across the SFR-M$_{*}$ plane. We find low-velocity outflows to be prevalent in regions of high SFRs and stellar masses (10 $\lesssim$log M$_{*}$/M$_{\odot}$ $\lesssim$ 11.5), however we do not find any detections in the low mass (log M$_{*}$/M$_{\odot}$ $\lesssim$ 10) regime. We also find tentative detections of inflowing gas in high mass galaxies across the star-forming population. We derive mass outflow rates in the range of 0.14-1.74\,M$_{\odot}$yr$^{-1}$ and upper limits on inflow rates <1\,M$_{\odot}$yr$^{-1}$, allowing us to place constraints on the mass loading factor ($\eta$=$\dot{M}_{\text{out}}$/SFR) for use in simulations of the local Universe. We discuss the fate of the outflows by comparing the force provided by the starburst to the critical force needed to push the outflow outward, and find the vast majority of the outflows unlikely to escape the host system. Finally, as outflow detection rates and central velocities do not vary strongly with the presence of a (weak) active supermassive black hole, we determine that star formation appears to be the primary driver of outflows at $z\sim$0.Comment: Accepted in MNRAS. 36 pages, 15 figure

Accelerating Parallel Tempering: Quantile Tempering Algorithm (QuanTA)

Using MCMC to sample from a target distribution, $\pi(x)$ on a $d$-dimensional state space can be a difficult and computationally expensive problem. Particularly when the target exhibits multimodality, then the traditional methods can fail to explore the entire state space and this results in a bias sample output. Methods to overcome this issue include the parallel tempering algorithm which utilises an augmented state space approach to help the Markov chain traverse regions of low probability density and reach other modes. This method suffers from the curse of dimensionality which dramatically slows the transfer of mixing information from the auxiliary targets to the target of interest as $d \rightarrow \infty$. This paper introduces a novel prototype algorithm, QuanTA, that uses a Gaussian motivated transformation in an attempt to accelerate the mixing through the temperature schedule of a parallel tempering algorithm. This new algorithm is accompanied by a comprehensive theoretical analysis quantifying the improved efficiency and scalability of the approach; concluding that under weak regularity conditions the new approach gives accelerated mixing through the temperature schedule. Empirical evidence of the effectiveness of this new algorithm is illustrated on canonical examples